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Record W1983228020 · doi:10.2514/6.2010-9014

What Would Industry Like to See Covered in the Capstone Design Course?

2010· article· en· W1983228020 on OpenAlexaff
Leland M. Nicolai, Eric Schrock

Bibliographic record

Venue10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference · 2010
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsCourse (navigation)CapstoneEngineeringComputer scienceManufacturing engineeringEngineering managementSoftware engineeringComputer securityAerospace engineering

Abstract

fetched live from OpenAlex

I. Abstract The senior level capstone design course should be conducted like a realistic conceptual design study in industry. This means an RFP, design reviews, students working in small IPT groups (4-5 people working as an integrated product team) with the opportunity to embrace a realistic open ended problem and operate as an engineering team. The course should be at least two semesters in duration to provide opportunities for a thorough understanding of the design process and time for design iterations. Finally, the essence of realism is in the results – the students must make realistic design estimates throughout the design study and be expected to make engineering decisions and execute them. During the initial phases of the design analysis, students should be required to use back of the envelope (BOE) analysis to develop an intuitive feel for the results and to eliminate dependence on the computer. It is especially discouraging to see students base their entire design effort on design estimates that are wrong. They must be taught to do a “sanity check” on every estimate they make. Handbook methods, coupled with sanity checks using historical data, should form the basis of early vehicle sizing during the first months of the design course. Emphasis must also be placed on the general arrangement of the configuration. University curricula are structured almost exclusively around analysis and not on engineering design. By the time students reach their senior year, most of them do not have a grasp on practical aircraft design. Time should be spent using hand drawing techniques to quickly trade different aircraft configuration arrangements. Hand drawing is essential so that students are not limited by varying degrees of CAD proficiency. Once students have mastered basic sizing and configuration layout principles, more sophisticated analysis methods can be brought to bear but should be limited to those that provide quick turnaround (i.e. vortex lattice tools and not full blown CFD). When it is clear that the student is generating realistic design data the student should conduct parametric trade studies to size the concepts to requirements and determine the sensitivity of the design to changes in the design parameters, mission

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.528
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.283
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2010
Admission routes1
Has abstractyes

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